Control Charts for Multivariate Nonlinear Time Series
In this paper control charts for the simultaneous monitoring of the means and the variances of multivariate nonlinear time series are introduced. The underlying target process is assumed to be a constant conditional correlation process (cf. [3]). The new schemes make use of local measures of the mea...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Robert Garthoff [verfasserIn] Iryna Okhrin [verfasserIn] Wolfgang Schmid [verfasserIn] |
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| Format: |
E-Artikel |
|---|---|
| Sprache: |
Englisch |
| Erschienen: |
2015 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
In: Revstat Statistical Journal - Instituto Nacional de Estatística | Statistics Portugal, 2022, 13(2015), 2 |
|---|---|
| Übergeordnetes Werk: |
volume:13 ; year:2015 ; number:2 |
| Links: |
Link aufrufen |
|---|
| DOI / URN: |
10.57805/revstat.v13i2.168 |
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DOAJ07888537X |
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| 520 | |a In this paper control charts for the simultaneous monitoring of the means and the variances of multivariate nonlinear time series are introduced. The underlying target process is assumed to be a constant conditional correlation process (cf. [3]). The new schemes make use of local measures of the means and the variances based on current observations, conditional moments, or residuals. Exponential smoothing and cumulative sums are applied to these characteristic quantities. Distances between these quantities and target values are measured by the Mahalanobis distance. The introduced schemes are compared via a simulation study. As a measure of performance the average run length is used. | ||
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10.57805/revstat.v13i2.168 doi (DE-627)DOAJ07888537X (DE-599)DOAJb37f45b2aa5146e6a0c9e5216b6a9d3c DE-627 ger DE-627 rakwb eng HA1-4737 QA273-280 Robert Garthoff verfasserin aut Control Charts for Multivariate Nonlinear Time Series 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In this paper control charts for the simultaneous monitoring of the means and the variances of multivariate nonlinear time series are introduced. The underlying target process is assumed to be a constant conditional correlation process (cf. [3]). The new schemes make use of local measures of the means and the variances based on current observations, conditional moments, or residuals. Exponential smoothing and cumulative sums are applied to these characteristic quantities. Distances between these quantities and target values are measured by the Mahalanobis distance. The introduced schemes are compared via a simulation study. As a measure of performance the average run length is used. statistical process control multivariate CUSUM charts multivariate EWMA charts conditional correlation model Statistics Probabilities. Mathematical statistics Iryna Okhrin verfasserin aut Wolfgang Schmid verfasserin aut In Revstat Statistical Journal Instituto Nacional de Estatística | Statistics Portugal, 2022 13(2015), 2 (DE-627)DOAJ078597773 21830371 nnns volume:13 year:2015 number:2 https://doi.org/10.57805/revstat.v13i2.168 kostenfrei https://doaj.org/article/b37f45b2aa5146e6a0c9e5216b6a9d3c kostenfrei https://revstat.ine.pt/index.php/REVSTAT/article/view/168 kostenfrei https://doaj.org/toc/1645-6726 Journal toc kostenfrei https://doaj.org/toc/2183-0371 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ AR 13 2015 2 |
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In this paper control charts for the simultaneous monitoring of the means and the variances of multivariate nonlinear time series are introduced. The underlying target process is assumed to be a constant conditional correlation process (cf. [3]). The new schemes make use of local measures of the means and the variances based on current observations, conditional moments, or residuals. Exponential smoothing and cumulative sums are applied to these characteristic quantities. Distances between these quantities and target values are measured by the Mahalanobis distance. The introduced schemes are compared via a simulation study. As a measure of performance the average run length is used. |
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In this paper control charts for the simultaneous monitoring of the means and the variances of multivariate nonlinear time series are introduced. The underlying target process is assumed to be a constant conditional correlation process (cf. [3]). The new schemes make use of local measures of the means and the variances based on current observations, conditional moments, or residuals. Exponential smoothing and cumulative sums are applied to these characteristic quantities. Distances between these quantities and target values are measured by the Mahalanobis distance. The introduced schemes are compared via a simulation study. As a measure of performance the average run length is used. |
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In this paper control charts for the simultaneous monitoring of the means and the variances of multivariate nonlinear time series are introduced. The underlying target process is assumed to be a constant conditional correlation process (cf. [3]). The new schemes make use of local measures of the means and the variances based on current observations, conditional moments, or residuals. Exponential smoothing and cumulative sums are applied to these characteristic quantities. Distances between these quantities and target values are measured by the Mahalanobis distance. The introduced schemes are compared via a simulation study. As a measure of performance the average run length is used. |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000naa a22002652 4500</leader><controlfield tag="001">DOAJ07888537X</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230307011923.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">230307s2015 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.57805/revstat.v13i2.168</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)DOAJ07888537X</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)DOAJb37f45b2aa5146e6a0c9e5216b6a9d3c</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="050" ind1=" " ind2="0"><subfield code="a">HA1-4737</subfield></datafield><datafield tag="050" ind1=" " ind2="0"><subfield code="a">QA273-280</subfield></datafield><datafield tag="100" ind1="0" ind2=" "><subfield code="a">Robert Garthoff</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Control Charts for Multivariate Nonlinear Time Series</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2015</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">In this paper control charts for the simultaneous monitoring of the means and the variances of multivariate nonlinear time series are introduced. The underlying target process is assumed to be a constant conditional correlation process (cf. [3]). The new schemes make use of local measures of the means and the variances based on current observations, conditional moments, or residuals. Exponential smoothing and cumulative sums are applied to these characteristic quantities. Distances between these quantities and target values are measured by the Mahalanobis distance. The introduced schemes are compared via a simulation study. 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